Application of Big Data for Medical Data Analysis Using Hadoop Environment

  • M. S. Roobini
  • M. LakshmiEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)


Big Data (BDA) is progressively turning into a slanting practice that numerous associations are receiving with the motivation behind developing important data from Big Data. The term Big Data is likewise used to catch the openings and difficulties confronting all scientists in overseeing, examining, and incorporating datasets of differing information compose. In this paper we mention how the healthcare factor become more advance in modern world. This includes that the health care data should be properly analyzed so that we can deduce that in which group or gender, diseases attack the most. This beneficial outputs which include: getting the health care analysis in various forms. Thus this concept of analytics should be implemented with a view of future use. Beyond improving profits and cutting down on wasted overhead, Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. With the world’s population increasing and everyone living longer, models of treatment delivery are rapidly changing, and many of the decisions behind those changes are being driven by data. The drive now is to understand as much about a patient as possible, as early in their life as possible hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later.


  1. 1.
    Agrawal, D., et al.: Challenges and opportunities with big data. In: Big Data - White Paper. Computing Research Association (2012)Google Scholar
  2. 2.
    Chen, H., Chiang, H.L., Storey, C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36(4), 1–24 (2012)CrossRefGoogle Scholar
  3. 3.
    Liyanage, H., de Lusignan, S., Liaw, S.T., Kuziemsky, C., Mold, F., Krause, P., Fleming, D., Jones, S.: Big data usage patterns in the health care domain: a use case driven approach applied to the assessment of vaccination benefits and risks. Yearb. Med. Inform. 9(1), 27–35 (2014)Google Scholar
  4. 4.
    Peek, N., Holmes, J.H., Sun, J.: Technical challenges for big data in biomedicine and health: data sources, infrastructure, and analytics. Yearb. Med. Inform. 9(1), 42–47 (2014)Google Scholar
  5. 5.
    Krishnan, S.: Application of analytics to big data in healthcare. In: Southern Biomedical Engineering Conference (2016)Google Scholar
  6. 6.
    Koppad, S.H., Kumar, A.: Application of big data analytics in healthcare system to predict COPD. In: International Conference on Circuit, Power and Computing Technologies (2016)Google Scholar
  7. 7.
    Tang, S., Lee, B.-S., He, B.: DynamicMR: a dynamic slot allocation optimized framework for MapReduced clusters. IEEE Trans. (2013)Google Scholar
  8. 8.
    Hou, B., Li, K.Q.L., Shi, Y., Tao, L., Liu, J.: MongoDB NoSQL injection analysis and detection. In: International Conference on Cyber Security and Cloud Computing (2016)Google Scholar
  9. 9.
    Adil, A., Kar, H.A., Jangir, R., Sofi, S.A.: Analysis of multi-diseases using big data for improvement in healthcare. In: Electrical Computer and Electronics. IEEE (2015)Google Scholar
  10. 10.
    Agrawal, D., Bemstein, P., Bertino, E.: Big data White pdf. November 2011–February 2012Google Scholar
  11. 11.
    Bhosale, H.S., Gadekar, D.P.: A review paper on big data and hadoop. Int. J. Sci. Res. Publ. 4(10), 1–7 (2014)Google Scholar
  12. 12.
    Dhyani, B., Barthwal, A.: Big data analytics using hadoop. Int. J. Comput. Appl. 108(12) (2014). 0975-8887CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Sathyabama Institute of Science and TechnologyChennaiIndia

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